Re: [Gimp-developer] AI algorithms in GIMP

Hi people,

1. Laxminarayan has some very good suggestions. I think all of them are
possible with varying degree of success.
2. Liam, I am implementing a quite popular paper for image upscaling called
3. Gerald, there would be a testing and validation datasets to gauge the
accuracy of the neural network. The goal would be to minimize 'overfitting'
of the neural network to the training dataset. You're going to lose quality
when you upscale, but the upscaled images will still be better than ones
produced using traditional algorithms.

Sorry I haven't been able to get back to you guys before, I am caught up in
work and will not be able to write code properly till something important
gets over. However, I have studied generative adversarial networks (GANs)
and am now learning a python ML library called PyTorch. Once this is done,
I'll be able to start writing code. My main problem here seems to be the
computational infraastructure, I fear that my 8 GB Nvidia Quadro M4000 will
not be good enough to train on the data. If anybody had better resources
they can share, please let me know.

Once we have the toy GAN code set up in Python, people can play around with
it for various types of projects.


On Sat, Mar 30, 2019 at 8:44 PM Gerald Friedland via gimp-developer-list <
gimp-developer-list gnome org> wrote:


When people say "AI" here do they mean Neural Networks?

"Intelligent" algorithms have been implemented in GIMP for many years.
About 15 years ago, this algorithm got integrated into GIMP:

Now, the reason I bring this is up is that any machine learning algorithm
needs extensive empirical testing and we setup frameworks for
that during the integration of the above algorithm. So whatever machine
learning you want to integrate in GIMP needs to come with an
independent benchmark dataset that is annotated for what you want to
achieve. This benchmark dataset is used AFTER you think you
are ready with building your algorithm.
This is, after you have trained and tested your machine learner (using yet
completely different datasets) and minimized parameters
for generalization, the benchmark dataset does not only further test
accuracy and generalization but also computational efficiency
and user experience. Question like how can the user correct errors of the
AI need to be answered too.

On a further note, if you did this benchmark testing, you would find that
waifu2x is scam. This is, it only works with a very specialized
set of images. The first thing to investigate would be what set of images
that is and how to explain that to a GIMP user. In general, images
cannot be upscaled. The data processing inequality mathematically proofs
that information cannot be created by processing an image.
So, while many TV crime shows suggest this, algorithmically zooming into a
blurry license plate or face to make it recognizable is physically
and mathematically impossible. An independent benchmark set would show the
limits of this algorithm.

Just my two cents,

On Fri, Mar 29, 2019 at 8:58 PM Liam R E Quin <liam holoweb net> wrote:

On Sat, 2019-03-30 at 07:40 +0530, Laxminarayan Kamath via gimp-
developer-list wrote:
just dropping a couple of ideas here


Something like waifu2x would be fabulous to have in GIMP (a neural
network-based image upscaling algorithm).

slave liam (ankh on IRC)

Liam Quin - web slave for
with fabulous vintage art and fascinating texts to read.
Click here to have the slave rewarded with cold gruel.

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